code: def train_unsupervised(self, inputs, unsup_coef):
      # Train the unsupervised model here
      self._validate_training_mode()
  
      outputs = self.actor_model(**inputs, use_cache=False)
      loss = outputs.loss
      self.actor_model.backward(unsup_coef * loss)
      self.actor_model.step()
  
      return loss
  
imports: import torch
  import torch.nn.functional
  import time
  import deepspeed
  from deepspeed.runtime.zero.partition_parameters import ZeroParamStatus
  from deepspeed.accelerator import get_accelerator
  from dschat.utils.utils import print_rank_0
label_desc: Use image node_id 2 for calling the DeepSpeedPPOTrainerUnsupervised obj's underlying member method code with example usage: obj.train_unsupervised(inputs, unsup_coef) and returns: loss